AIMC Topic: Area Under Curve

Clear Filters Showing 661 to 670 of 1194 articles

An improved fuzzy-differential evolution approach applied to classification of tumors in liver CT scan images.

Medical & biological engineering & computing
Fuzzy inference systems have been frequently used in medical diagnosis for managing uncertainty sources in the medical images. In addition, fuzzy systems have high level of interpretability because of using linguistic terms for knowledge representati...

A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England)
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...

Novel deep learning model for more accurate prediction of drug-drug interaction effects.

BMC bioinformatics
BACKGROUND: Predicting the effect of drug-drug interactions (DDIs) precisely is important for safer and more effective drug co-prescription. Many computational approaches to predict the effect of DDIs have been proposed, with the aim of reducing the ...

Comparison between logistic regression and machine learning algorithms on survival prediction of traumatic brain injuries.

Journal of critical care
PURPOSE: To compare twenty-two machine learning (ML) models against logistic regression on survival prediction in severe traumatic brain injury (STBI) patients in a single center study.

Machine learning to predict cardiovascular risk.

International journal of clinical practice
AIMS: To analyse the predictive capacity of 15 machine learning methods for estimating cardiovascular risk in a cohort and to compare them with other risk scales.

Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).

Journal of biomedical informatics
AIM: The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical softwa...

Evaluation of machine learning methods with Fourier Transform features for classifying ovarian tumors based on ultrasound images.

PloS one
INTRODUCTION: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasound examination has become the main technique for assessment of ovarian pathology and for preoperative distinction between malignant and benign ovarian...

Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.

Contrast media & molecular imaging
PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical intervention. Response to chemotherapy, however, is affected by intratumor heterogeneity. In this study, we assessed the ability of a machine learning ...

Development and rigorous validation of antimalarial predictive models using machine learning approaches.

SAR and QSAR in environmental research
The large collection of known and experimentally verified compounds from the ChEMBL database was used to build different classification models for predicting the antimalarial activity against . Four different machine learning methods, namely the supp...